Learn R Programming

nparcomp (version 3.0)

Multiple Comparisons and Simultaneous Confidence Intervals

Description

With this package, it is possible to compute nonparametric simultaneous confidence intervals for relative contrast effects in the unbalanced one way layout. Moreover, it computes simultaneous p-values. The simultaneous confidence intervals can be computed using multivariate normal distribution, multivariate t-distribution with a Satterthwaite Approximation of the degree of freedom or using multivariate range preserving transformations with Logit or Probit as transformation function. 2 sample comparisons can be performed with the same methods described above. There is no assumption on the underlying distribution function, only that the data have to be at least ordinal numbers. See Konietschke et al. (2015) for details.

Copy Link

Version

Install

install.packages('nparcomp')

Monthly Downloads

561

Version

3.0

License

GPL

Maintainer

Last Published

June 25th, 2019

Functions in nparcomp (3.0)

summary.nparcomp

plot.nparcomp

summary.mctp

appetite

Appetite scores of colorectal cancer patients
plot.nparttest

summary.mctp.rm

plot.mctp.rm

plot.mctp

summary.nparttestpaired

nparcomp

Nonparametric relative contrast effects
panic

Clinical Global Impression (CGI) Scores
npar.t.test.paired

A 2-sample nonparametric studentized permutation test for paired data
summary.nparttest

reaction

Reaction times of mice [sec]
plot.nparttestpaired

nparcomp-package

Nparcomp: Nonparametric relative contrast effects.
impla

Numbers of implantations
npar.t.test

The nonparametric Behrens-Fisher problem
mctp

Nonparametric multiple contrast tests and simultaneous confidence intervals (independent samples)
liver

Relative liver weights
mctp.rm

Nonparametric multiple contrast tests and simultaneous confidence intervals (repeated measures)
PGI

Patient Rated Global Impression (PGI) Scores
gao_cs

Nonparametric multiple test procedure for all-pairs comparisons
colu

Numbers of corpora lutea
gao

Nonparametric multiple test procedure for many-to-one comparisons